Behavior arbitration for autonomous mobile robots using emotion mechanisms

Conventional AI (artificial intelligence) technology has been criticized on many drawbacks such as brittleness under dynamically changing environments. To overcome this problem, other approaches called behavior-based AI, new AI, emergent computation, animat approach and so on were proposed and confirmed their usefulness. Since computational ability of mobile robots is limited in general, it is required that robots extract feasible information from their environment for appropriate behavior control by themselves. On the other hand, in living organisms, there are mainly two systems to cope with dynamically changing environment: 1) immune system, and 2) emotional system. Based on this fact, in this paper, we present a new method of behavior arbitration mechanisms for autonomous mobile robots by paying close attention to emotional system in living organisms. We confirm the feasibility of our proposed method by applying to an obstacle avoidance problem of a mobile robot as a practical example